Peer Review

Deep Learning

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Overview:: Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. This resource material is an introductory course to Deep Learning.
Type of Material:: Open Textbook
Recommended Uses:: The course material can be used for in-class discussion, homework, lectures, self-paced learning for individuals or groups.
Technical Requirements:: Internet browser (e.g. IE, Safari, Chrome, Firefox, etc.)
Identify Major Learning Goals:: The key learning goal of the website is to provide course materials together with exercises for college students, undergraduates to postgraduates to have a basic yet comprehensive understanding of the deep learning techniques, their potential applications and research directions.
Target Student Population:: The course material is designed for senior college students or undergraduates, or postgraduates who are very interested to know more about machine learning, esp. the latest development in deep learning. It is also appropriate for faculty members and special interest groups.
Prerequisite Knowledge or Skills:: 1. Familiarity with programming 2. Basic understanding of computational performance issues 3. Complexity Theory 4. Introductory level calculus 5. Graph Theory terminology

Rating:
Strengths:: 1. This resource provides a complete demonstration of the Deep Learning concept 2. The resource is current and supported by appropriate research 3. Overall, the quality of content in this textbook is very high
Concerns:: 1. The resource is not self-contained 2. Except for chapter 2, the textbook lacks exercises

Rating:
Strengths:: 1. The textbook identifies learning objectives and prerequisite knowledge 2. The textbook reinforces concepts progressively, builds on prior concepts and demonstrates relationships between concepts In summary, the material together with the exercises is effective as a teaching tool to facilitate learners' fundamental understanding of the basic working of the various deep learning techniques and their potential applications in different fields.
Concerns:: Nil.

Rating:
Strengths:: This resource on deep learning is engaging, visually appealing and easy to follow. The usability of this set of course material is high as it contains lecture materials together with exercises for learners to review their understanding.
Concerns:: 1. The resource is only accessible via HTML. There is no provision for PDF format 2. The resource is not interactive

Other Issues and Comments:: The material is very helpful and useful for any new learners, practitioners or researchers who try to understand more about the emerging fields of deep learning.
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